Myth-making machines - Analysing generative AI’s visual stories of climate change

Sammanfattning

Despite generative Artificial Intelligence’s (AI) explosive growth in popularity and record of biased outputs, little attention has been paid to the technology’s potential to shape perceptions around sustainability. This analysis investigates which perceptions about climate change causes, impacts and solutions are visually naturalised or marginalised by three text-to-image AI models: GPT‑4o, Ideogram, and Imagen. Guided by Barthes’ conceptualisation of semiotics and myth, and integrating content and semiotic analysis, a dataset of 960 images was coded for recurring visual elements. The emerging patterns revealed the pictures to tell six distinct myths, largely aligning with an ecological modernisation approach. A second step of analysis focusing on counter-narratives revealed only GPT‑4o to be able to create outputs strongly challenging the mainstream. These findings suggest a risk of generative AI hindering sustainability transformations by contributing to a visual climate change discourse that naturalises insufficient mainstream approaches and suppresses urgently needed alternatives. Solutions are explored.